论文标题
内源性和异质需求模型中随机系数的非参数鉴定
Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand Models
论文作者
论文摘要
本文研究了与异质消费者的差异化产品的市场水平需求模型中的非参数识别。我们考虑了一类通用模型，该模型允许各个特定系数在整个人群中连续变化，并给出这些系数密度的条件，从而确定了诸如福利措施之类的功能。一个关键发现是，两个领先的模型BLP模型（Berry，Levinsohn和Pakes，1995年）和纯特征模型（Berry and Pakes，2007年），在支持产品特征的支持下需要大大不同的条件。
This paper studies nonparametric identification in market level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual specific coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also functionals such as welfare measures, is identified. A key finding is that two leading models, the BLP-model (Berry, Levinsohn, and Pakes, 1995) and the pure characteristics model (Berry and Pakes, 2007), require considerably different conditions on the support of the product characteristics.
